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Pathogen-Specific Local Immune Fingerprints Diagnose Bacterial Infection in Peritoneal Dialysis Patients

免疫系统 免疫学 腹膜透析 腹膜炎 病菌 生物 医学 内科学
作者
Chan‐Yu Lin,Gareth Roberts,Matt Morgan,Kieron Donovan,Nicholas Topley,Matthias Eberl
出处
期刊:Journal of The American Society of Nephrology [American Society of Nephrology]
卷期号:24 (12): 2002-2009 被引量:57
标识
DOI:10.1681/asn.2013040332
摘要

Accurate and timely diagnosis of bacterial infection is crucial for effective and targeted treatment, yet routine microbiological identification is inefficient and often delayed to an extent that makes it clinically unhelpful. The immune system is capable of a rapid, sensitive and specific detection of a broad spectrum of microbes, which has been optimized over millions of years of evolution. A patient's early immune response is therefore likely to provide far better insight into the true nature and severity of microbial infections than conventional tests. To assess the diagnostic potential of pathogen-specific immune responses, we characterized the local responses of 52 adult patients during episodes of acute peritoneal dialysis (PD)–associated peritonitis by multicolor flow cytometry and multiplex ELISA, and defined the immunologic signatures in relation to standard microbiological culture results and to clinical outcomes. We provide evidence that unique local “immune fingerprints” characteristic of individual organisms are evident in PD patients on the day of presentation with acute peritonitis and discriminate between culture-negative, Gram-positive, and Gram-negative episodes of infection. Those humoral and cellular parameters with the most promise for defining disease-specific immune fingerprints include the local levels of IL-1β, IL-10, IL-22, TNF-α, and CXCL10, as well as the frequency of local γδ T cells and the relative proportion of neutrophils and monocytes/macrophages among total peritoneal cells. Our data provide proof of concept for the feasibility of using immune fingerprints to inform the design of point-of-care tests that will allow rapid and accurate infection identification and facilitate targeted antibiotic prescription and improved patient management.

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